A Protocol for the Global Sensitivity Analysis of Impact Assessment Models in Life Cycle Assessment

Abstract

The life cycle assessment (LCA) framework has established itself as the leading tool for the assessment of the environmental impact of products. Several works have established the need of integrating the LCA and risk analysis methodologies, due to the several common aspects. One of the ways to reach such integration is through guaranteeing that uncertainties in LCA modeling are carefully treated. It has been claimed that more attention should be paid to quantifying the uncertainties present in the various phases of LCA. Though the topic has been attracting increasing attention of practitioners and experts in LCA, there is still a lack of understanding and a limited use of the available statistical tools. In this work, we introduce a protocol to conduct global sensitivity analysis in LCA. The article focuses on the life cycle impact assessment (LCIA), and particularly on the relevance of global techniques for the development of trustable impact assessment models. We use a novel characterization model developed for the quantification of the impacts of noise on humans as a test case. We show that global SA is fundamental to guarantee that the modeler has a complete understanding of: (i) the structure of the model and (ii) the importance of uncertain model inputs and the interaction among them.

Life cycle assessment of emerging technologies: A review

“…Global sensitivity analysis (GSA) are gaining attraction to evaluate the sensitivity of the LCA outputs to the entire input space. For more details about global sensitivity analysis, we refer Cucurachi, Borgonovo, and Heijungs () and Pérez‐lópez et al. (), Lacirignola, Blanc, Girard, Pérez‐López, and Blanc ().…”

Life cycle assessment of emerging technologies: Evaluation techniques at different stages of market and technical maturity

“…Some studies (Lacirignola, Blanc, Girard, Pérez‐López, & Blanc, ; Ravikumar et al., ) have proposed new methods for accounting for uncertainty in LCA of emerging technologies using sensitivity analyses to aid in identifying key parameters affecting a technology's environmental impacts. Integrated Assessment Models have been used to develop future demand scenarios to account for market conditions surrounding demand for current technologies (Mendoza Beltran et al., ) or deployment of emerging technologies (Cucurachi, Borgonovo, & Heijungs, ; Steubing, Reinhard, Zah, & Ludwig, ). Others have employed consequential modeling approaches to assess the net environmental effects of future increases in demand for a product such as renewable fuels (Reinhard & Zah, ; Reinhard & Zah, ).…”

Towards an optimal coverage of ecosystem services in LCA

“…Our prioritization analysis can serve as a guide for future research by indicating the ES categories that present the "highest priority" based on available monetary data. In addition, a high number of indicators may be considered difficult to handle in decision-making processes (Cucurachi et al, 2016). The weighting step in LCA has the explicit intention to address this problem by further aggregating the indicator results using normative weights and thus facilitate decision-making (Cucurachi et al, 2017).…”